22 resultados para Database application, Biologia cellulare, Image retrieval


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Introduction: Recently developed portable dental X-ray units increase the mobility of the forensic odontologists and allow more efficient X-ray work in a disaster field, especially when used in combination with digital sensors. This type of machines might also have potential for application in remote areas, military and humanitarian missions, dental care of patients with mobility limitation, as well as imaging in operating rooms. Objective: To evaluate radiographic image quality acquired by three portable X-ray devices in combination with four image receptors and to evaluate their medical physics parameters. Materials and methods: Images of five samples consisting of four teeth and one formalin-fixed mandible were acquired by one conventional wall-mounted X-ray unit, MinRay (R) 60/70 kVp, used as a clinical standard, and three portable dental X-ray devices: AnyRay (R) 60 kVp, Nomad (R) 60 kVp and Rextar (R) 70 kVp, in combination with a phosphor image plate (PSP), a CCD, or a CMOS sensor. Three observers evaluated images for standard image quality besides forensic diagnostic quality on a 4-point rating scale. Furthermore, all machines underwent tests for occupational as well as patient dosimetry. Results: Statistical analysis showed good quality imaging for all system, with the combination of Nomad (R) and PSP yielding the best score. A significant difference in image quality between the combination of the four X-ray devices and four sensors was established (p < 0.05). For patient safety, the exposure rate was determined and exit dose rates for MinRay (R) at 60 kVp, MinRay (R) at 70 kVp, AnyRay (R), Nomad (R) and Rextar (R) were 3.4 mGy/s, 4.5 mGy/s, 13.5 mGy/s, 3.8 mGy/s and 2.6 mGy/s respectively. The kVp of the AnyRay (R) system was the most stable, with a ripple of 3.7%. Short-term variations in the tube output of all the devices were less than 10%. AnyRay (R) presented higher estimated effective dose than other machines. Occupational dosimetry showed doses at the operator`s hand being lowest with protective shielding (Nomad (R): 0.1 mu Gy). It was also low while using remote control (distance > 1 m: Rextar (R) < 0.2 mu Gy, MinRay (R) < 0.1 mu Gy). Conclusions: The present study demonstrated the feasibility of three portable X-ray systems to be used for specific indications, based on acceptable image quality and sufficient accuracy of the machines and following the standard guidelines for radiation hygiene. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

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Multidimensional Visualization techniques are invaluable tools for analysis of structured and unstructured data with variable dimensionality. This paper introduces PEx-Image-Projection Explorer for Images-a tool aimed at supporting analysis of image collections. The tool supports a methodology that employs interactive visualizations to aid user-driven feature detection and classification tasks, thus offering improved analysis and exploration capabilities. The visual mappings employ similarity-based multidimensional projections and point placement to layout the data on a plane for visual exploration. In addition to its application to image databases, we also illustrate how the proposed approach can be successfully employed in simultaneous analysis of different data types, such as text and images, offering a common visual representation for data expressed in different modalities.

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A novel mathematical framework inspired on Morse Theory for topological triangle characterization in 2D meshes is introduced that is useful for applications involving the creation of mesh models of objects whose geometry is not known a priori. The framework guarantees a precise control of topological changes introduced as a result of triangle insertion/removal operations and enables the definition of intuitive high-level operators for managing the mesh while keeping its topological integrity. An application is described in the implementation of an innovative approach for the detection of 2D objects from images that integrates the topological control enabled by geometric modeling with traditional image processing techniques. (C) 2008 Published by Elsevier B.V.

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The analysis of histological sections has long been a valuable tool in the pathological studies. The interpretation of tissue conditions, however, relies directly on visual evaluation of tissue slides, which may be difficult to interpret because of poor contrast or poor color differentiation. The Chromatic Contrast Visualization System (CCV) combines an optical microscope with electronically controlled light-emitting diodes (LEDs) in order to generate adjustable intensities of RGB channels for sample illumination. While most image enhancement techniques rely on software post-processing of an image acquired under standard illumination conditions, CCV produces real-time variations in the color composition of the light source itself. The possibility of covering the entire RGB chromatic range, combined with the optical properties of the different tissues, allows for a substantial enhancement in image details. Traditional image acquisition methods do not exploit these visual enhancements which results in poorer visual distinction among tissue structures. Photodynamic therapy (PDT) procedures are of increasing interest in the treatment of several forms of cancer. This study uses histological slides of rat liver samples that were induced to necrosis after being exposed to PDT. Results show that visualization of tissue structures could be improved by changing colors and intensities of the microscope light source. PDT-necrosed tissue samples are better differentiated when illuminated with different color wavelengths, leading to an improved differentiation of cells in the necrosis area. Due to the potential benefits it can bring to interpretation and diagnosis, further research in this field could make CCV an attractive technique for medical applications.

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An entropy-based image segmentation approach is introduced and applied to color images obtained from Google Earth. Segmentation refers to the process of partitioning a digital image in order to locate different objects and regions of interest. The application to satellite images paves the way to automated monitoring of ecological catastrophes, urban growth, agricultural activity, maritime pollution, climate changing and general surveillance. Regions representing aquatic, rural and urban areas are identified and the accuracy of the proposed segmentation methodology is evaluated. The comparison with gray level images revealed that the color information is fundamental to obtain an accurate segmentation. (C) 2010 Elsevier B.V. All rights reserved.

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Purpose: We present an iterative framework for CT reconstruction from transmission ultrasound data which accurately and efficiently models the strong refraction effects that occur in our target application: Imaging the female breast. Methods: Our refractive ray tracing framework has its foundation in the fast marching method (FNMM) and it allows an accurate as well as efficient modeling of curved rays. We also describe a novel regularization scheme that yields further significant reconstruction quality improvements. A final contribution is the development of a realistic anthropomorphic digital breast phantom based on the NIH Visible Female data set. Results: Our system is able to resolve very fine details even in the presence of significant noise, and it reconstructs both sound speed and attenuation data. Excellent correspondence with a traditional, but significantly more computationally expensive wave equation solver is achieved. Conclusions: Apart from the accurate modeling of curved rays, decisive factors have also been our regularization scheme and the high-quality interpolation filter we have used. An added benefit of our framework is that it accelerates well on GPUs where we have shown that clinical 3D reconstruction speeds on the order of minutes are possible.

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The design of translation invariant and locally defined binary image operators over large windows is made difficult by decreased statistical precision and increased training time. We present a complete framework for the application of stacked design, a recently proposed technique to create two-stage operators that circumvents that difficulty. We propose a novel algorithm, based on Information Theory, to find groups of pixels that should be used together to predict the Output Value. We employ this algorithm to automate the process of creating a set of first-level operators that are later combined in a global operator. We also propose a principled way to guide this combination, by using feature selection and model comparison. Experimental results Show that the proposed framework leads to better results than single stage design. (C) 2009 Elsevier B.V. All rights reserved.